Deep transfer learning radiomics combined with explainable machine learning for preoperative thymoma risk prediction based on CT.

Journal: European journal of radiology
Published Date:

Abstract

OBJECTIVE: To develop and validate a computerized tomography (CT)‑based deep transfer learning radiomics model combined with explainable machine learning for preoperative risk prediction of thymoma.

Authors

  • Shujian Wu
    Department of Radiology, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Lifang Fan
    School of Medical Imageology, Wannan Medical College, Wuhu, 241002, Anhui, China.
  • Yimin Wu
    Department of Ultrasound, The Second People's Hospital, WuHu Hospital, East China Normal University, Wuhu, Anhui, 241001, China.
  • Jingya Xu
    Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, 430070, Wuhan, Hubei, P.R. China.
  • Yong Guo
    Department of Urology, The First Hospital of Shijiazhuang, Shijiazhuang 050011, China.
  • Hu Zhang
    Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China.
  • Zhengyuan Xu
    Department of Medical Engineering, Wannan Medical College, WuHu, AnHui, 241002, China. xuzy@wnmc.edu.cn.